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  • Induction

    ID check and visa checkpoint information for new students starting at the University of Leicester.

  • Key financial information

    Key financial information about the University of Leicester, including our legal and charity status, financial details, banking arrangements, and management and governance.

  • Andrew Hyam BSc MA

    Learn more about our Senior Supervisor of ULAS, Andrew Hyam.

  • Advanced Statistical Modelling (Part-time)

    Module code: MD7468 Generalised linear models This module will start by introducing the theory of generalized linear models (GLMs) in terms of exponential family of distributions and discussing special cases of GLMs, such as normal, Poisson or binomial regression.

  • BSc Project Practical

    Module code: CH3261 You are now coming to the end of your BSc studies here at Leicester, and your practical chemistry skills will have developed immensely. The BSc Project Practical will enable you to put your hard work into practice.

  • Research

    Basic mechanisms and processes Injury Coagulation following injury Injury Epidemiology Injury Prevention Trauma System Organisation Illness identification DDU (Descriptive Studies) EMBER Children's emergency care DDU (Paeds Descriptive...

  • Fundamentals of Data Science

    Module code: MA7419 Data science is the process of extracting reliable insights and conclusions from data.

  • Fundamentals of Data Science

    Module code: MA3419 Data science is the process of extracting reliable insights and conclusions from data.

  • Advanced Statistical Modelling (Part-time)

    Module code: MD7468 Generalised linear models This module will start by introducing the theory of generalized linear models (GLMs) in terms of exponential family of distributions and discussing special cases of GLMs, such as normal, Poisson or binomial regression.

  • Advanced Statistical Modelling (Part-time)

    Module code: MD7468 Generalised linear models This module will start by introducing the theory of generalized linear models (GLMs) in terms of exponential family of distributions and discussing special cases of GLMs, such as normal, Poisson or binomial regression.

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